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Network Growth Model ------------------- The relevant script is kept in the folder bipartite_growth. The following are parameters to the script, parallel.py. 1. \mu - u 2. \gamma - y 3. n 4. t The script runs in various mode which are: 1. Run the parallel attachment with replacement 2. Run the parallel attachment without replacement 3. Run the sequential attachment model 4. Generate theoretical model for sequential attachment model Currently the way to run the script is rather obscure. The values can be easily modified in the main function( at the end ), though running various models requires some knowledge of code. TODO: Change all the running variations in command line and document. Directory Structure ------------------- The script requires to have a folder, "datasets" w.r.t to it's execution location. No other specific requirement exists. Dependencies ------------ Depends heavily on Numpy( python Numberical Framework ) and networkx( Python Network Analysis Framework ). Running Info ----------- This script under, crawlRunning.py crawls information about currently running trains for IRN. The sample can be seen at: http://www.trainenquiry.com/indexNS.aspx. The current script iterates over train numbers, and for each train all it's stations. The data crawled is in the format: Train, Station, Date, Expected Arrival, Expected Departure, Actual Arrival and Actual Departure. Hence it captures the essence network delay. It can be extremely useful for some of the Network Analysis. Directory Structure ------------------ The end of script specifies the directory name. It is currently of the format crawl-yyyy-mm-dd Dependencies ------------ Packages: BeautifulSoup for parsing the HTML files Data: TrainStation information in the format of Train and the Stations it stops at. How to run --------- python crawlRunning.py TrainStation_2010.txt NODEBUG old NODEBUG - Defaul mode to be used while crawling old - It specifies that the train numbers are in old format, used in the TrainStation2010.txt file.